Data Engineer with Snowflake

Job Title: Data EngineerExperience: 5–9 yearsLocation: [Remote]Job Summary:We are looking for a skilled Data Engineer with strong expertise in Python, PySpark, AWS services (Glue, Lambda), and Snowflake. The ideal candidate will design, build, and maintain scalable data pipelines, ensure efficient data integration, and enable advanced analytics and reporting across the organization.Key Responsibilities:Design, develop, and optimize ETL/ELT pipelines using Python, PySpark, and AWS Glue.Implement data ingestion, transformation, and integration from diverse structured and unstructured sources.Work extensively with Snowflake for data modeling, performance tuning, and query optimization.Automate workflows and data processing using AWS Lambda and other AWS-native services.Ensure data quality, consistency, and security across data platforms.Collaborate with data scientists, analysts, and business teams to deliver scalable data solutions.Monitor, troubleshoot, and improve the performance of data pipelines.Maintain proper documentation of data flows, processes, and best practices.Required Skills & Qualifications:4–9 years of proven experience as a Data Engineer or similar role.Strong programming skills in Python and hands-on experience with PySpark.Expertise in AWS services – Glue, Lambda, S3, CloudWatch, IAM, etc.Proficiency in Snowflake – data modeling, warehouse design, query optimization.Solid understanding of ETL/ELT concepts, data warehousing, and big data processing.Strong knowledge of SQL and performance tuning.Experience with version control (Git), CI/CD pipelines, and deployment best practices.Knowledge of data governance, security, and compliance.Excellent problem-solving, communication, and collaboration skills

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